Datasets:
Modalities:
Text
Formats:
parquet
Sub-tasks:
semantic-similarity-classification
Size:
1M - 10M
Tags:
paraphrase-generation
License:
| annotations_creators: | |
| - machine-generated | |
| language_creators: | |
| - crowdsourced | |
| languages: | |
| - af | |
| - ar | |
| - az | |
| - be | |
| - ber | |
| - bg | |
| - bn | |
| - br | |
| - ca | |
| - cbk | |
| - cmn | |
| - cs | |
| - da | |
| - de | |
| - el | |
| - en | |
| - eo | |
| - es | |
| - et | |
| - eu | |
| - fi | |
| - fr | |
| - gl | |
| - gos | |
| - he | |
| - hi | |
| - hr | |
| - hu | |
| - hy | |
| - ia | |
| - id | |
| - ie | |
| - io | |
| - is | |
| - it | |
| - ja | |
| - jbo | |
| - kab | |
| - ko | |
| - kw | |
| - la | |
| - lfn | |
| - lt | |
| - mk | |
| - mr | |
| - nb | |
| - nds | |
| - nl | |
| - orv | |
| - ota | |
| - pes | |
| - pl | |
| - pt | |
| - rn | |
| - ro | |
| - ru | |
| - sl | |
| - sr | |
| - sv | |
| - tk | |
| - tl | |
| - tlh | |
| - toki | |
| - tr | |
| - tt | |
| - ug | |
| - uk | |
| - ur | |
| - vi | |
| - vo | |
| - war | |
| - wuu | |
| - yue | |
| licenses: | |
| - cc-by-2.0 | |
| multilinguality: | |
| - multilingual | |
| size_categories: | |
| - 100K<n<1M | |
| - 10K<n<100K | |
| - 1K<n<10K | |
| - 1M<n<10M | |
| - n<1K | |
| source_datasets: | |
| - extended|other-tatoeba | |
| task_categories: | |
| - text2text-generation | |
| - translation | |
| - text-classification | |
| task_ids: | |
| - text2text-generation-other-paraphrase-generation | |
| - semantic-similarity-classification | |
| paperswithcode_id: tapaco | |
| pretty_name: TaPaCo Corpus | |
| configs: | |
| - af | |
| - all_languages | |
| - ar | |
| - az | |
| - be | |
| - ber | |
| - bg | |
| - bn | |
| - br | |
| - ca | |
| - cbk | |
| - cmn | |
| - cs | |
| - da | |
| - de | |
| - el | |
| - en | |
| - eo | |
| - es | |
| - et | |
| - eu | |
| - fi | |
| - fr | |
| - gl | |
| - gos | |
| - he | |
| - hi | |
| - hr | |
| - hu | |
| - hy | |
| - ia | |
| - id | |
| - ie | |
| - io | |
| - is | |
| - it | |
| - ja | |
| - jbo | |
| - kab | |
| - ko | |
| - kw | |
| - la | |
| - lfn | |
| - lt | |
| - mk | |
| - mr | |
| - nb | |
| - nds | |
| - nl | |
| - orv | |
| - ota | |
| - pes | |
| - pl | |
| - pt | |
| - rn | |
| - ro | |
| - ru | |
| - sl | |
| - sr | |
| - sv | |
| - tk | |
| - tl | |
| - tlh | |
| - toki | |
| - tr | |
| - tt | |
| - ug | |
| - uk | |
| - ur | |
| - vi | |
| - vo | |
| - war | |
| - wuu | |
| - yue | |
| # Dataset Card for TaPaCo Corpus | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [TaPaCo: A Corpus of Sentential Paraphrases for 73 Languages](https://zenodo.org/record/3707949#.X9Dh0cYza3I) | |
| - **Paper:** [TaPaCo: A Corpus of Sentential Paraphrases for 73 Languages](https://www.aclweb.org/anthology/2020.lrec-1.848.pdf) | |
| - **Point of Contact:** [Yves Scherrer](https://blogs.helsinki.fi/yvesscherrer/) | |
| ### Dataset Summary | |
| A freely available paraphrase corpus for 73 languages extracted from the Tatoeba database. | |
| Tatoeba is a crowdsourcing project mainly geared towards language learners. Its aim is to provide example sentences | |
| and translations for particular linguistic constructions and words. The paraphrase corpus is created by populating a | |
| graph with Tatoeba sentences and equivalence links between sentences “meaning the same thing”. This graph is then | |
| traversed to extract sets of paraphrases. Several language-independent filters and pruning steps are applied to | |
| remove uninteresting sentences. A manual evaluation performed on three languages shows that between half and three | |
| quarters of inferred paraphrases are correct and that most remaining ones are either correct but trivial, | |
| or near-paraphrases that neutralize a morphological distinction. The corpus contains a total of 1.9 million | |
| sentences, with 200 – 250 000 sentences per language. It covers a range of languages for which, to our knowledge, | |
| no other paraphrase dataset exists. | |
| ### Supported Tasks and Leaderboards | |
| Paraphrase detection and generation have become popular tasks in NLP | |
| and are increasingly integrated into a wide variety of common downstream tasks such as machine translation | |
| , information retrieval, question answering, and semantic parsing. Most of the existing datasets | |
| cover only a single language – in most cases English – or a small number of languages. Furthermore, some paraphrase | |
| datasets focus on lexical and phrasal rather than sentential paraphrases, while others are created (semi | |
| -)automatically using machine translation. | |
| The number of sentences per language ranges from 200 to 250 000, which makes the dataset | |
| more suitable for fine-tuning and evaluation purposes than | |
| for training. It is well-suited for multi-reference evaluation | |
| of paraphrase generation models, as there is generally not a | |
| single correct way of paraphrasing a given input sentence. | |
| ### Languages | |
| The dataset contains paraphrases in Afrikaans, Arabic, Azerbaijani, Belarusian, Berber languages, Bulgarian, Bengali | |
| , Breton, Catalan; Valencian, Chavacano, Mandarin, Czech, Danish, German, Greek, Modern (1453-), English, Esperanto | |
| , Spanish; Castilian, Estonian, Basque, Finnish, French, Galician, Gronings, Hebrew, Hindi, Croatian, Hungarian | |
| , Armenian, Interlingua (International Auxiliary Language Association), Indonesian, Interlingue; Occidental, Ido | |
| , Icelandic, Italian, Japanese, Lojban, Kabyle, Korean, Cornish, Latin, Lingua Franca Nova\t, Lithuanian, Macedonian | |
| , Marathi, Bokmål, Norwegian; Norwegian Bokmål, Low German; Low Saxon; German, Low; Saxon, Low, Dutch; Flemish, ]Old | |
| Russian, Turkish, Ottoman (1500-1928), Iranian Persian, Polish, Portuguese, Rundi, Romanian; Moldavian; Moldovan, | |
| Russian, Slovenian, Serbian, Swedish, Turkmen, Tagalog, Klingon; tlhIngan-Hol, Toki Pona, Turkish, Tatar, | |
| Uighur; Uyghur, Ukrainian, Urdu, Vietnamese, Volapük, Waray, Wu Chinese and Yue Chinese | |
| ## Dataset Structure | |
| ### Data Instances | |
| Each data instance corresponds to a paraphrase, e.g.: | |
| ``` | |
| { | |
| 'paraphrase_set_id': '1483', | |
| 'sentence_id': '5778896', | |
| 'paraphrase': 'Ɣremt adlis-a.', | |
| 'lists': ['7546'], | |
| 'tags': [''], | |
| 'language': 'ber' | |
| } | |
| ``` | |
| ### Data Fields | |
| Each dialogue instance has the following fields: | |
| - `paraphrase_set_id`: a running number that groups together all sentences that are considered paraphrases of each | |
| other | |
| - `sentence_id`: OPUS sentence id | |
| - `paraphrase`: Sentential paraphrase in a given language for a given paraphrase_set_id | |
| - `lists`: Contributors can add sentences to list in order to specify the original source of the data | |
| - `tags`: Indicates morphological or phonological properties of the sentence when available | |
| - `language`: Language identifier, one of the 73 languages that belong to this dataset. | |
| ### Data Splits | |
| The dataset is having a single `train` split, contains a total of 1.9 million sentences, with 200 – 250 000 | |
| sentences per language | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed] | |
| ### Licensing Information | |
| Creative Commons Attribution 2.0 Generic | |
| ### Citation Information | |
| ``` | |
| @dataset{scherrer_yves_2020_3707949, | |
| author = {Scherrer, Yves}, | |
| title = {{TaPaCo: A Corpus of Sentential Paraphrases for 73 Languages}}, | |
| month = mar, | |
| year = 2020, | |
| publisher = {Zenodo}, | |
| version = {1.0}, | |
| doi = {10.5281/zenodo.3707949}, | |
| url = {https://doi.org/10.5281/zenodo.3707949} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@pacman100](https://github.com/pacman100) for adding this dataset. | |